Abstract
Existing methods on sample size calculations for right-censored data largely assume the failure times follow exponential distribution or the Cox proportional hazards model. Methods under the additive hazards model are scarce. Motivated by a well known example of right-censored failure time data which the additive hazards model fits better than the Cox model, we proposed a method for power and sample size calculation for a two-group comparison assuming the additive hazards model. This model allows the investigator to specify a group difference in terms of a hazard difference and choose increasing, constant or decreasing baseline hazards. The power computation is based on the Wald test. Extensive simulation studies are performed to demonstrate the performance of the proposed approach. Our simulation also shows substantially decreased power if the additive hazards models is misspecified as the Cox proportional hazards model.
Highlights
The Cox proportional hazards (PH) model (Cox, 1972) has become the standard tool and routinely used in the analysis of survival data
As the motivation of this paper, we present a well-known example of rightcensored failure time data which can be fit better by the additive hazards model than the Cox model
We propose a power and sample size calculation based on the Wald test
Summary
The Cox proportional hazards (PH) model (Cox, 1972) has become the standard tool and routinely used in the analysis of survival data. A two-sided test for departure from the additive hazards model yields a Z-score −1.13 (p-value = 0.258) These tests provide strong evidence that the Additive hazards model is a better fit than the Cox model in describing the effect of 6-MP on the hazard of remission time in patients with acute leukemia. Based on these pilot data, if clinicians would like to design a pivotal study to compare 6-MP to placebo where the outcome is time to remission in patients with acute leukemia, a method for sample size or power calculation under the additive hazards model is warranted.
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